In 2009, our research team received funding from the National Institute of Justice (NIJ), a component of the U.S. Department of Justice, in cooperation with the Chicago Police Department. In this competition, cities were challenged to develop and evaluate new methods of predictive crime analysis, the aim being to provide crime reduction efforts with software tools to assist in data-driven decision-making, as has been done successfully in business, medicine, and other fields.

As part of this research program, we have developed a statistical technique called the Crime and Victimization Risk Model (CVRM), which seeks to determine an individual's risk for involvement in violence. The goal for the model is to help to prioritize resources in crime-prevention efforts. For example, the model can help social-services assistance programs to determine to who is at greatest risk, so that the programs can best prioritize their limited resources.

We have also developed algorithms that forecast the number of violent crimes that will occur tomorrow citywide, and per police district, and we have created algorithms that make maps showing where crimes of various kinds are most likely to occur. The purpose of these techniques is to help police to best allocate patrol resources based on anticipated short-term crime patterns.

Finally, under another National Institute of Justice grant, we are conducting a statistical evaluation study to determine the extent to which the use of outdoor security cameras actually reduces crime in their vicinity.